Arne De Keyser

Perceptions are relative: An examination of the relationship between relative satisfaction metrics and share of wallet

Purpose – There is general agreement among researchers and practitioners that satisfaction is relative to competitive alternatives. Nonetheless, researchers and managers have not treated satisfaction as a relative construct. The result has been weak relationships between satisfaction and share of wallet in the literature, and challenges by managers as to whether satisfaction is a useful predictor of customer behavior and business outcomes. The purpose of this paper is to explore the best approach for linking satisfaction to share of wallet. Design/methodology/approach – Using data from 79,543 consumers who provided 258,743 observations regarding the brands that they use (over 650 brands) covering 20 industries from 15 countries, various models such as the Wallet Allocation Rule (WAR), Zipf-AE, and Zipf-PM, truncated geometric model, generalization of the WAR and hierarchical regression models are compared to each other. Findings – The results indicate that the relationship between satisfaction and share o...

How technical and functional service quality drive consumer happiness: Moderating influences of channel usage

Purpose - This study aims to investigate the impact of technical (i.e. what is delivered) and functional (i.e. how is it delivered) service quality on consumer happiness in a multichannel environment. In so doing, this study responds to increasing calls from academics (e.g. transformative service research movement) and practitioners to move beyond pure financial measures when deciding how to manage businesses. Design/methodology/approach - With a sample of 809 customers of a medium-sized Belgian mail order firm, within-class regression models tested for the moderating role of channel usage. Findings - Both technical and functional service quality have positive impacts on consumer happiness. However, depending on the channel(s) used, the quality dimension that has the greatest impact on consumer happiness differs. Practical implications - The findings offer managers insights on how they can create and cultivate consumer happiness by delivering excellent service quality. This study stresses the importance of looking beyond purely financial measures to manage firms, and as such deliver value to consumers, the firm itself and society at large. Originality/value - This study advances transformative service research by being one of the few empirical studies relating service quality to consumer happiness in todays multichannel environment.

Customer intentions to invoke service guarantees: Do excellence in service recovery, type of guarantee, and cultural orientation matter?

Purpose – Many service providers feel confident about their service quality and thus offer service guarantees to their customers. Yet service failures are inevitable. As guarantees can only be invoked when customers report service failures, firms are given the opportunity to redress the original failure potentially influencing customer outcomes. The purpose of this paper is to provide the first empirical investigation of whether excellence in service recovery affects customers’ intentions to invoke a service guarantee, thereby discriminating between conditional and unconditional guarantees and testing for the impact of customers’ individualistic vs collectivistic cultural orientation. Design/methodology/approach – In total, 171 respondents from four continents (spanning 23 countries) were recruited to participate in a quasi-experimental study in a hotel setting. A three-way analysis of variance was used to test the hypotheses. Findings – All customers are very likely to invoke the service guarantee after ...

Customer engagement through personalization and customization

This chapter examines how tailored marketing strategies in the form of customization and personalization can foster customer engagement along the customer lifecycle. Building on various real-world examples, the authors outline the general array of opportunities that companies have at their disposal to customize and/or personalize the marketing mix. In addition, they discuss important contingency factors that facilitate or impede the applicability of both strategies under various business circumstances.

Data-Driven Optimal Power Flow Management in an Electric Dual-Drive Topology for Vehicle Electrification

The limited operating range on a single charge can be seen as an important detriment to contemporary vehicular technology, necessitating regular charging of the battery pack. Due to the high load variability during driving, incorporating two different electric motors in the drive can provide significant improvements in terms of energy consumption. A data-driven approach towards optimal power flow management in such configuration is proposed. Computationally expensive dynamic models are translated into an equivalent power flow-based representation, taking into account peak start-up losses. Optimal synchronization of both machines is then assessed over a given drive cycle, providing an optimal actuation policy for all embodied subsystems. Modifications to a standard dynamic programming formulation are introduced, reducing the computation time by a factor 125. The dual-drive topology furthermore offers the capability of cutting down energy consumption by 19.9%. Notable range extensions can thus be achieved by intelligently formulating and tackling the power flow management problem in a dual-drive topology.

Adaptive state space representations enabling reliable and robust decision-making in asynchronous drives for mechatronic applications

In contemporary mechatronic applications decision-making is often based on information about the underlying model governing the dynamical evolution, in order to ensure optimal operation with respect to a prioritized objective. Modeling errors stemming from parameter uncertainty or varying operational conditions result in inevitable deviations from the theoretical estimate and consequently in suboptimal operation. Intelligent systems need to be equipped with inherent means to compensate for these a priori unknown discrepancies, hereby guaranteeing a robust operation in uncertain environments. In this manuscript, advanced filtering techniques are applied to assess both an optimal model representation and state estimates. An appropriate interconnection between both model and state estimation is determined. The proposed methodology is demonstrated for an electric drive, embodying a DC-source, a voltage source inverter (VSI) and an asynchronous machine, as the presence of discrete switching sequences and physical constraints introduces additional challenges. Results prove that the error on the state estimates can be improved by 92.7–97.2%, outperforming the classical estimation techniques, while the relative model mismatch is scaled down to 0.03%, even in highly demanding scenarios. The introduced strategy thus enables high-fidelity virtual sensing and reliable decision-making procedures for advanced asynchronous drives when modeling errors can be anticipated.

Convex Mapping Formulations Enabling Optimal Power Split and Design of the Electric Drivetrain in All-Electric Vehicles

All-electric drivetrains have been identified as a promising alternative to contemporary hybrid vehicle technology. Extending their operational range is key and can be achieved by means of design procedures based on high-fidelity models capturing the dynamical behavior of the electric drivetrain. This paper proposes a dedicated power split embodying a dual electric drive and a model-based strategy to design the drivetrain. Advancements are required in model-based design that can cope with the complexity of the computationally expensive and high-dimensional parametric design problems. We propose a nested optimization approach wherein parameter exploration is attained using an evolutionary algorithm and the optimal power flows are determined by abstracting the high-fidelity behavioral models into appropriate convex loss mappings. This allows for an accelerated design procedure based on convex optimization without compromising accuracy. We size an electric drivetrain for maximal range extension, consisting of a battery stack, buck–boost converter, inverter and mechanically coupled induction motors subjected to variable load conditions. A tractable convex formulation is obtained and optimization time is reduced by 99.3% compared to the traditional approach without convexification. Optimal control of the incorporated power split increases the operational range by 0.7% compared to the isolated operation of a single motor. The proposed methodology thus paves the way for extensive designs of drivetrains and complex mechatronic systems in a general context.